Abstract
Crude oil spills have negative consequences on the economy, environment, health and society in which they occur, and the severity of the consequences depends on how quickly these spills are detected once they begin. Several methods have been employed for spill detection, including real time remote surveillance by flying aircrafts with surveillance teams. Other methods employ various sensors, including visible sensors. This paper presents an algorithm to automatically detect the presence of crude oil spills in images acquired using visible light sensors. Images of crude oil spills used in the development of the algorithm were obtained from the Shell Petroleum Development Company (SPDC) Nigeria website The major steps of the detection algorithm are image preprocessing, crude oil color segmentation, sky elimination segmentation, Region of Interest (ROI) extraction, ROI texture feature extraction, and ROI texture feature analysis and classification. The algorithm was developed using 25 sample images containing crude oil spills and demonstrated a sensitivity of 92% and an FPI of 1.43. The algorithm was further tested on a set of 56 case images and demonstrated a sensitivity of 82% and an FPI of 0.66. This algorithm can be incorporated into spill detection systems that utilize visible sensors for early detection of crude oil spills.
Highlights
Crude oil spills have severe negative effects on the environment, health, society and economy of the nation in which they occur, and this has been documented extensively in scientific literature [1,2,3,4,5,6,7,8,9,10].In the United States, 217 spill incidents were reported and 43,662 barrels (6,942,258 L) spilled in2007 [11]
Company (SPDC) Nigeria website The major steps of the detection algorithm are image preprocessing, crude oil color segmentation, sky elimination segmentation, Region of Interest (ROI) extraction, ROI texture feature extraction, and ROI texture feature analysis and classification
The algorithm was further tested on a set of 56 case images and demonstrated a sensitivity of 82% and an False Positives per Image (FPI) of 0.66
Summary
Crude oil spills have severe negative effects on the environment, health, society and economy of the nation in which they occur, and this has been documented extensively in scientific literature [1,2,3,4,5,6,7,8,9,10].In the United States, 217 spill incidents were reported and 43,662 barrels (6,942,258 L) spilled in2007 [11]. Crude oil spills have severe negative effects on the environment, health, society and economy of the nation in which they occur, and this has been documented extensively in scientific literature [1,2,3,4,5,6,7,8,9,10]. Resources of Nigeria reported a total of 871 spill incidents and 15,552.18 bbl (2,472,796.6 L) of oil released into the environment in 2012 [13]. When a spill occurs in water or offshore, contact and ingestion of spilled oil leads to contaminants in tissues, DNA damage, impacts to immune functioning, cardiac dysfunction, mass mortality of eggs and larvae, and the loss of buoyancy and insulation for birds [14,15,16,17,18,19,20,21]. Other effects include contamination of ground water, loss of biodiversity in breeding grounds, vegetation hazards, loss of portable and industrial water resources, reduction in fishing and farming activity, poverty and rural underdevelopment [24]
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